Title :
Unscented Particle Filter algorithm based on artificial fish swarm algorithm
Author :
Tian, Yu-min ; Chen, Li
Author_Institution :
Res. Inst. of Comput. Peripherals, Xidian Univ., Xi´´an, China
Abstract :
Aiming at the problem of Unscented Particle Filter (UPF) algorithm such as particles degeneracy and particles impoverishment, by use of the behaviors of preying, swarming and following in the artificial fish swarm algorithm, an artificial fish swarm algorithm is used to make the particles of UKF move toward the global optimum, which optimalizes the resampling process and relieves the problem of particles degeneracy and impoverishment. Experiments show that this algorithm improves the estimation accuracy of UPF algorithm.
Keywords :
Kalman filters; particle filtering (numerical methods); particle swarm optimisation; UKF; artificial fish swarm algorithm; particles degeneracy; particles impoverishment; preying behavior; resampling process optimisation; swarming behavior; unscented Kalman filter; unscented particle filter algorithm; Algorithm design and analysis; Fellows; Filtering algorithms; Marine animals; Particle filters; Signal processing algorithms; Artificial Fish Swarm Algorithm; Unscented Particle Filter; particles impoverishment; resampling;
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234707